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Modelling extreme rainfall in Kenya

Fredrick Muhindi, George Kingori Maina

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Naturwissenschaften, Medizin, Informatik, Technik / Geografie

Beschreibung

Research Paper (postgraduate) from the year 2022 in the subject Geography / Earth Science - Meteorology, Aeronomy, Climatology, , course: Social Science in Statistics, language: English, abstract: Occurrence of extreme rainfall has increased globally for couple of years, causing a lot of damages that affect the aspects of life such as, economic, environmental, social and physical. Different researchers have used different methods to model extreme rainfall around the globe. For example Generalized Extreme Value (GEV) and time series. This project focuses on modelling extreme rainfall in the areas Nyeri, Kericho Mombasa Nairobi and Kakamega. There are areas which are more prone to heavy rains, using rainfall data for the past 20 years to model extreme rainfall pattern in Kenya. We have used generalized Pareto distribution (GPD) to model extreme rainfall and have used time series to show the pattern and forecast the occurrence of extreme rainfall in Kenya. From forecasted result, we found that for the year 2016-2018 monthly rainfall tend to increase and decrease randomly this could be as a result of changes in climate due to global warming.

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Schlagwörter

Stationality, ARIMA, Heteroscedastic, MA, ARMA, Ljung box, Ducky-fuller, Diagonistics, Trends, Differencing, Box Jekins